Explicit Characterization of Feedback Capacity for Continuous-Time ARMA(1,1) Gaussian Channel
The feedback capacity of the continuous-time ARMA(1,1) Gaussian channel is explicitly characterized. It is shown that feedback may not increase the capacity of this channel, unlike the discrete-time case.
Deterministic Identification Codes for Fading Channels: Achieving Reliable Communication in Challenging Environments
The authors investigate deterministic identification (DI) codes for Gaussian AWGN, slow fading, and fast fading channels, proving new lower and upper bounds on the capacity of these channels. They show that DI codes can achieve significantly different capacity scaling compared to traditional Shannon message transmission, making them well-suited for event-triggered communication in next-generation wireless networks.
Optimizing Variable-Length Stop-Feedback Coding for Minimum Age of Incorrect Information
This work analyzes the minimum achievable average Age of Incorrect Information (AoII) in the non-asymptotic regime, where the impact of feedback time instances for variable-length stop-feedback (VLSF) codes is investigated.
Analyzing LIGHTCODE: Neural Codes for Channels with Feedback
Designing lightweight neural codes like LIGHTCODE and analytical schemes like POWERBLAST can outperform existing deep-learning-based codes for channels with feedback.
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